Why Fortran Is Still Used

3 hours ago

Fortran is specialized for high-performance computing and remains relevant due to its performance-centric culture.
It is easier to use than C/C++ for scientific computing, with native support for multidimensional arrays and complex numbers.
Fortran guarantees code longevity and backward compatibility, allowing decades-old code to still compile and run.
Coarrays introduced in Fortran 2008 provide intrinsic distributed-memory parallelism, simplifying parallel code development.
Fortran continues to evolve with active standardization and community efforts, such as Fortran-lang.org and LFortran.

Static assert allows compile-time checks and self-documenting code.
constexpr enables compile-time computation, improving performance and reducing runtime overhead.
std::numeric_limits provides uniform access to type limits, replacing macros like ULLONG_MAX.

Tungsten is an object-oriented language designed for clarity and mathematical expression, with syntax that resembles whiteboard pseudocode.
It compiles to native binaries via LLVM and GPU kernels via Metal, using a self-hosted compiler.
Key features include first-class support for currency (dollars, cents, percentages) and units (meters, kilograms) with automatic conversion and dimensional analysis.

Differentiable Fortran allows backpropagation through existing Fortran, C, or C++ simulation code using LFortran and Enzyme, enabling integration with modern ML frameworks like JAX and PyTorch.
Enzyme applies autodifferentiation at the LLVM IR level, allowing differentiation of any code that compiles to LLVM, avoiding the need to rewrite validated legacy physics code.
LFortran is used instead of Flang because it emits cleaner LLVM IR with plain pointer arithmetic, making it easier for Enzyme to trace memory accesses without opaque runtime calls.

Modern C++ compilers (like Clang and GCC) can produce optimal code from naive implementations, making many old performance tricks obsolete.
Fast inverse square root, once a clever optimization for old CPUs, is now comparable to naive implementations thanks to compiler and hardware advances.
Standard library features like <bit> for popcount, ranges, and algorithms offer clear, portable code that often matches or beats hand-optimized versions.

The ntoskrnl-rs project successfully rewrote the Windows NT kernel in Rust, booting in QEMU and passing self-tests.
Claude Fable 5 generated the core kernel (about 5,100 lines) in 38 minutes, including scheduling, memory management, and I/O subsystems.
The kernel loads unmodified Windows drivers and binaries, providing a sandbox for analysis and debugging.

Static assert allows compile-time checks and self-documenting code.
constexpr enables compile-time computation, improving performance and reducing runtime overhead.
std::numeric_limits provides uniform access to type limits, replacing macros like ULLONG_MAX.

Tungsten is an object-oriented language designed for clarity and mathematical expression, with syntax that resembles whiteboard pseudocode.
It compiles to native binaries via LLVM and GPU kernels via Metal, using a self-hosted compiler.
Key features include first-class support for currency (dollars, cents, percentages) and units (meters, kilograms) with automatic conversion and dimensional analysis.

Differentiable Fortran allows backpropagation through existing Fortran, C, or C++ simulation code using LFortran and Enzyme, enabling integration with modern ML frameworks like JAX and PyTorch.
Enzyme applies autodifferentiation at the LLVM IR level, allowing differentiation of any code that compiles to LLVM, avoiding the need to rewrite validated legacy physics code.
LFortran is used instead of Flang because it emits cleaner LLVM IR with plain pointer arithmetic, making it easier for Enzyme to trace memory accesses without opaque runtime calls.

Modern C++ compilers (like Clang and GCC) can produce optimal code from naive implementations, making many old performance tricks obsolete.
Fast inverse square root, once a clever optimization for old CPUs, is now comparable to naive implementations thanks to compiler and hardware advances.
Standard library features like <bit> for popcount, ranges, and algorithms offer clear, portable code that often matches or beats hand-optimized versions.

The ntoskrnl-rs project successfully rewrote the Windows NT kernel in Rust, booting in QEMU and passing self-tests.
Claude Fable 5 generated the core kernel (about 5,100 lines) in 38 minutes, including scheduling, memory management, and I/O subsystems.
The kernel loads unmodified Windows drivers and binaries, providing a sandbox for analysis and debugging.

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